Trusted aggregation with data privacy based on zero-knowledge-proofs

ABSTRACT

A processor may commit, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway. The processor may generate a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator. The processor may execute individual commitments of a resource to a user. The processor may provide a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer and the Merkle tree hash commitment match.

BACKGROUND

The present disclosure relates generally to the field of data privacy, and more specifically to protecting data of contributors based on zero-knowledge-proofs (ZKPs).

In the electricity market there is a need for change, known as the energy transition, to include more renewable energy sources. These renewable energy devices are installed in large setups, and small setups, like rooftop solar and behind the meter batteries. Currently there is a growing market for energy service companies that optimize the assets for a given user with rooftop solar and behind the meter batteries. The energy service companies compete for the business model, e.g., how to best operate the individual assets. The device utilization data is considered as commercial private data.

SUMMARY

Embodiments of the present disclosure include a method, system, and computer program for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof. A processor may commit, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway. The processor may generate a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator. The processor may execute individual commitments of a resource to a user. The processor may provide a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer and the Merkle tree hash commitment match.

The above summary is not intended to describe each illustrated embodiment or every implementation of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings included in the present disclosure are incorporated into, and form part of, the specification. They illustrate embodiments of the present disclosure and, along with the description, serve to explain the principles of the disclosure. The drawings are only illustrative of certain embodiments and do not limit the disclosure.

FIG. 1A illustrates an example blockchain architecture, in accordance with embodiments of the present disclosure.

FIG. 1B illustrates a blockchain transactional flow, in accordance with embodiments of the present disclosure.

FIG. 2A illustrates an example of a decentralized fair marketplace, in accordance with embodiments of the present disclosure.

FIG. 2B illustrates an example of a ZKP based protocol for proving correct execution of contracts, in accordance with embodiments of the present disclosure.

FIG. 2C illustrates an example of a Merkle tree commitment of overall performance and individual user commitments, in accordance with embodiments of the present disclosure.

FIG. 3 illustrates a flowchart of an example method for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof, in accordance with embodiments of the present disclosure.

FIG. 4A illustrates a cloud computing environment, in accordance with embodiments of the present disclosure.

FIG. 4B illustrates abstraction model layers, in accordance with embodiments of the present disclosure.

FIG. 5 illustrates a high-level block diagram of an example computer system that may be used in implementing one or more of the methods, tools, and modules, and any related functions, described herein, in accordance with embodiments of the present disclosure.

While the embodiments described herein are amenable to various modifications and alternative forms, specifics thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the particular embodiments described are not to be taken in a limiting sense. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure.

DETAILED DESCRIPTION

Aspects of the present disclosure relate generally to the field of data privacy, and more specifically to protecting data of contributors based on zero-knowledge-proofs (ZKPs). In the electricity market there is a need for change, known as the energy transition, to include more renewable energy sources. These renewable energy devices are installed in large setups, and small setups, like rooftop solar and behind the meter batteries. Currently there is a growing market for energy service companies that optimize the assets for a given user with rooftop solar and behind the meter batteries. The energy service companies compete for the business model, e.g., how to best operate the individual assets. The device utilization data is considered as commercial private data.

Transmission System Operators (TSOs) are opening up their ancillary markets to aggregators, e.g., energy service companies, to supply energy flexibility. This is attractive for energy service companies as they access a new revenue stream by participating on these markets. However, the TSO's are demanding full transparency down to the device utilization level. Energy service companies are reluctant to disclose their business model by sharing device utilization data. This invention solves such tension by providing proof to the TSO, as market operator, while shielding device utilization data.

Discussed herein is a solution that ensures secure and anonymous bundling of a resource (e.g., energy, devices, etc.) according to a predefined agreement (e.g., smart contract) between an aggregator and a buyer (e.g., user), by enabling the resource aggregator to securely provide zero-knowledge-proofs to the resource buyer(s) where the resource bundling agreement specifications are met without any double utilization on the aggregator part and without revealing identity or other characteristics of the resource producers themselves. Further, the solution can be applied to energy markets where the resources correspond to small energy devices, aggregators manage a pool of these devices, and buyers can be transmission system operators or independent system operators.

In such a solution, a resource producer's identity, and associated data (e.g., clients, destinations, etc.), are committed anonymously on a blockchain by an independent gateway where the commitments are hash commitments. In some embodiments, an aggregator makes a Merkle tree hash commitment of all resources handled by the aggregator to the blockchain, where such a commitment involves the resource identity and its corresponding performance, and where a sub-tree in the Merkle tree corresponds to a commitment of individual resources. In some embodiments, the aggregator makes individual commitments of a resource supply to a buyer/user.

In some embodiments, the aggregator provides: a zero-knowledge-proof that the commitments made of the resource supply to the buyer/user are consistent with the overall commitment made in regard to the Merkle tree hash commitment of all resources handled by the aggregator; and also a (second) zero-knowledge-proof that the commitments are mutually exclusive with no double utilization. In some embodiments, the aggregator provides a (third) zero-knowledge-proof that the agreement specifications of the buyer are met without revealing the identity or data characteristics of individual resource producers. In some embodiments, any of the zero-knowledge proofs could be the same zero-knowledge proof.

Before turning to the FIGS., it will be readily understood that the instant components, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Accordingly, the following detailed description of the embodiments of at least one of a method, apparatus, non-transitory computer readable medium and system, as represented in the attached figures, is not intended to limit the scope of the application as claimed but is merely representative of selected embodiments.

The instant features, structures, or characteristics as described throughout this specification may be combined or removed in any suitable manner in one or more embodiments. For example, the usage of the phrases “example embodiments,” “some embodiments,” or other similar language, throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment. Accordingly, appearances of the phrases “example embodiments,” “in some embodiments,” “in other embodiments,” or other similar language, throughout this specification do not necessarily all refer to the same group of embodiments, and the described features, structures, or characteristics may be combined or removed in any suitable manner in one or more embodiments. Further, in the FIGS., any connection between elements can permit one-way and/or two-way communication even if the depicted connection is a one-way or two-way arrow. Also, any device depicted in the drawings can be a different device. For example, if a mobile device is shown sending information, a wired device could also be used to send the information.

In addition, while the term “message” may have been used in the description of embodiments, the application may be applied to many types of networks and data. Furthermore, while certain types of connections, messages, and signaling may be depicted in exemplary embodiments, the application is not limited to a certain type of connection, message, and signaling.

Additionally, while the terms transaction, transaction proposal, or proposal may be used throughout this description, it is noted that they may be interchangeable and are synonymous with a blockchain transaction/transaction proposal, which is not to be construed as a business or financial transaction. As a transaction proposal in regard to blockchain is a proposal to commit data to the blockchain and a transaction in regard to blockchain is said commitment of data or is an execution of a smart contract code that can be performed in response to conditions associated with the smart contract being satisfied.

Detailed herein are a method, system, and computer program product that provide a trusted aggregation with data privacy of contributors based on a zero-knowledge-proof.

In some embodiment, the method, system, and/or computer program product utilize a decentralized database (such as a blockchain) that is a distributed storage system, which includes multiple nodes that communicate with each other. The decentralized database may include an append-only immutable data structure resembling a distributed ledger capable of maintaining records between mutually untrusted parties. The untrusted parties are referred to herein as peers, node, and/or peer nodes. Each peer maintains a copy of the database records and no single peer can modify the database records without a consensus being reached among the distributed peers. For example, the peers may execute a consensus protocol to validate blockchain storage transactions, group the storage transactions into blocks, and build a hash chain over the blocks. This process forms the ledger by ordering the storage transactions, as is necessary, for consistency.

In various embodiments, a permissioned and/or a permission-less blockchain can be used. In a public, or permission-less, blockchain, anyone can participate without a specific identity (e.g., retaining anonymity). Public blockchains can involve native cryptocurrency and use consensus based on various protocols such as Proof of Work. On the other hand, a permissioned blockchain database provides secure interactions among a group of entities which share a common goal but which do not fully trust one another, such as businesses that exchange funds, goods, (private) information, and the like.

Further, in some embodiment, the method, system, and/or computer program product can utilize a blockchain that operates arbitrary, programmable logic, tailored to a decentralized storage scheme and referred to as “smart contracts” or “chaincodes.” In some cases, specialized chaincodes may exist for management functions and parameters which are referred to as system chaincode (such as managing a ordering/serialization of transactions to be committed to a blockchain network). In some embodiments, the method, system, and/or computer program product can further utilize smart contracts that are trusted distributed applications which leverage tamper-proof properties of the blockchain database and an underlying agreement between nodes, which is referred to as an endorsement or endorsement policy.

An endorsement policy allows chaincode to specify endorsers for a transaction in the form of a set of peer nodes that are necessary for endorsement. When a client sends the transaction to the peers (e.g., endorsers) specified in the endorsement policy, the transaction is executed to validate the transaction. After validation, the transactions enter an ordering phase in which a consensus protocol is used to produce an ordered sequence of endorsed transactions grouped into blocks.

In some embodiment, the method, system, and/or computer program product can utilize nodes that are the communication entities of the blockchain system. A “node” may perform a logical function in the sense that multiple nodes of different types can run on the same physical server. Nodes are grouped in trust domains and are associated with logical entities that control them in various ways. Nodes may include different types, such as a client or submitting-client node which submits a transaction-invocation to an endorser (e.g., peer), and broadcasts transaction-proposals to an ordering service (e.g., ordering node).

Another type of node is a peer node which can receive client submitted transactions, commit the transactions, and maintain a state and a copy of the ledger of blockchain transactions. Peers can also have the role of an endorser, although it is not a requirement. An ordering-service-node or orderer is a node running the communication service for all nodes, and which implements a delivery guarantee, such as a broadcast to each of the peer nodes in the system when committing/confirming transactions and modifying a world state of the blockchain, which is another name for the initial blockchain transaction which normally includes control and setup information.

In some embodiment, the method, system, and/or computer program product can utilize a ledger that is a sequenced, tamper-resistant record of all state transitions of a blockchain. State transitions may result from chaincode invocations (e.g., transactions) submitted by participating parties (e.g., client nodes, ordering nodes, endorser nodes, peer nodes, etc.). Each participating party (such as a peer node) can maintain a copy of the ledger. A transaction may result in a set of asset key-value pairs being committed to the ledger as one or more operands, such as creates, updates, deletes, and the like. The ledger includes a blockchain (also referred to as a chain) which is used to store an immutable, sequenced record in blocks. The ledger also includes a state database that maintains a current state of the blockchain.

In some embodiment, the method, system, and/or computer program product described herein can utilize a chain that is a transaction log that is structured as hash-linked blocks, and each block contains a sequence of N transactions where N is equal to or greater than one. The block header includes a hash of the block's transactions, as well as a hash of the prior block's header. In this way, all transactions on the ledger may be sequenced and cryptographically linked together. Accordingly, it is not possible to tamper with the ledger data without breaking the hash links. A hash of a most recently added blockchain block represents every transaction on the chain that has come before it, making it possible to ensure that all peer nodes are in a consistent and trusted state. The chain may be stored on a peer node file system (e.g., local, attached storage, cloud, etc.), efficiently supporting the append-only nature of the blockchain workload.

The current state of the immutable ledger represents the latest values for all keys that are included in the chain transaction log. Since the current state represents the latest key values known to a channel, it is sometimes referred to as a world state. Chaincode invocations execute transactions against the current state data of the ledger. To make these chaincode interactions efficient, the latest values of the keys may be stored in a state database. The state database may be simply an indexed view into the chain's transaction log, it can therefore be regenerated from the chain at any time. The state database may automatically be recovered (or generated) upon peer node startup, and before transactions are accepted.

Some benefits of the instant solutions described and depicted herein include a method, system, and computer program product for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof. The exemplary embodiments solve the issues of tension between buyers/sellers by providing proof transactions/resources/supplies/etc. to a market operator, all while shielding device utilization data.

It is noted that blockchain is different from a traditional database in that blockchain is not a central storage, but rather a decentralized, immutable, and secure storage, where nodes may share in changes to records in the storage. Some properties that are inherent in blockchain and which help implement the blockchain include, but are not limited to, an immutable ledger, smart contracts, security, privacy, decentralization, consensus, endorsement, accessibility, and the like, which are further described herein. According to various aspects, the system described herein is implemented due to immutable accountability, security, privacy, permitted decentralization, availability of smart contracts, endorsements and accessibility that are inherent and unique to blockchain.

In particular, the blockchain ledger data is immutable, which provides for an efficient method for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof. Also, use of the encryption in the blockchain provides security and builds trust. The smart contract manages the state of the asset(s) to complete the life-cycle. The example blockchains are permission decentralized. Thus, each end user may have its own ledger copy to access. Multiple organizations (and peers) may be on-boarded on the blockchain network. The key organizations may serve as endorsing peers to validate the smart contract execution results, read-set, and write-set. In other words, the blockchain inherent features provide for efficient implementation of data privacy based on a zero-knowledge-proof, which in turn saves processing power and time related to processing the verification of information, and reduces strain on the blockchain network (e.g., the peers, nodes, components, etc.). As such, it is noted that the blockchain is not just a database; the blockchain comes with capabilities to create a network of users and to on-board/off-board organizations/entities/users to collaborate and execute service processes in the form of smart contracts, which may be associated energy consortiums and data privacy.

The example embodiments provide numerous benefits over a traditional database. For example, through the blockchain, the embodiments provide for immutable accountability, security, privacy, permitted decentralization, availability of smart contracts, endorsements and accessibility that are exclusive, and unique, to the blockchain. Without such benefits provided by blockchain, there would be unnecessary processing time and computing power wasted on the processing/verifying information.

Meanwhile, a traditional database could not be used to implement the example embodiments because it does not bring all parties on the network, it does not create trusted collaboration and does not provide for an efficient way to keep data privacy. The traditional database does not provide for tamper proof storage and does not provide for a means to avoid data leaks. Thus, the proposed embodiments described herein utilizing blockchain networks cannot be implemented by the traditional database; if a traditional database were to be used to implement the example embodiments, the example embodiments would have suffered from unnecessary drawbacks such as lack of security and slow data processing. Accordingly, the example embodiments provide for a specific solution to a problem in the arts/field of blockchain related data privacy.

Turning now to FIG. 1A, illustrated is a blockchain architecture 100, in accordance with embodiments of the present disclosure. In some embodiments, the blockchain architecture 100 may include certain blockchain elements, for example, a group of blockchain nodes 102. The blockchain nodes 102 may include one or more blockchain nodes, e.g., peers 104-110 (these four nodes are depicted by example only). These nodes participate in a number of activities, such as a blockchain transaction addition and validation process (consensus). One or more of the peers 104-110 may endorse and/or recommend transactions based on an endorsement policy and may provide an ordering service for all blockchain nodes 102 in the blockchain architecture 100. A blockchain node may initiate a blockchain authentication and seek to write to a blockchain immutable ledger stored in blockchain layer 116, a copy of which may also be stored on the underpinning physical infrastructure 114. The blockchain configuration may include one or more applications 124 which are linked to application programming interfaces (APIs) 122 to access and execute stored program/application code 120 (e.g., chaincode, smart contracts, etc.) which can be created according to a customized configuration sought by participants and can maintain their own state, control their own assets, and receive external information. This can be deployed as a transaction and installed, via appending to the distributed ledger, on all blockchain nodes 104-110.

The blockchain base or platform 112 may include various layers of blockchain data, services (e.g., cryptographic trust services, virtual execution environment, etc.), and underpinning physical computer infrastructure that may be used to receive and store new transactions and provide access to auditors which are seeking to access data entries. The blockchain layer 116 may expose an interface that provides access to the virtual execution environment necessary to process the program code and engage the physical infrastructure 114. Cryptographic trust services 118 may be used to verify transactions such as encryption and key generation and to keep information private.

The blockchain architecture 100 of FIG. 1A may process and execute program/application code 120 via one or more interfaces exposed, and services provided, by blockchain platform 112. The application code 120 may control blockchain assets. For example, the application code 120 can store and transfer data, and may be executed by peers 104-110 in the form of a smart contract and associated chaincode with conditions or other code elements subject to its execution. As a non-limiting example, smart contracts may be generated to execute the transfer of assets/resources, the generation of assets/resources, etc. The smart contracts can themselves be used to identify rules associated with authorization (e.g., asset transfer rules, restrictions, encryption/key generation, etc.), access requirements (e.g., of a datastore, of an off-chain datastore, of who may participate in a transaction, etc.), and/or usage of the ledger. For example, the ZKPs 126 (e.g., proving commitments without relinquishing confidential data) may be processed/examined by one or more processing entities (e.g., virtual machines) included in the blockchain layer 116. The result 128 may include a plurality of linked shared documents (e.g., with each linked shared document recording the ZKPs 126 as matching, being approved, etc.). In some embodiments, the physical infrastructure 114 may be utilized to retrieve any of the data/information/assets/etc. described herein.

A smart contract may be created via a high-level application and programming language, and then written to a block in the blockchain. The smart contract may include executable code which is registered, stored, and/or replicated with a blockchain (e.g., a distributed network of blockchain peers). A transaction is an execution of the smart contract code that can be performed in response to conditions associated with the smart contract being satisfied. The executing of the smart contract may trigger a trusted modification(s) to a state of a digital blockchain ledger. The modification(s) to the blockchain ledger caused by the smart contract execution may be automatically replicated throughout the distributed network of blockchain peers through one or more consensus protocols.

The smart contract may write data to the blockchain in the format of key-value pairs. Furthermore, the smart contract code can read the values stored in a blockchain and use them in application operations. The smart contract code can write the output of various logic operations into the blockchain. The code may be used to create a temporary data structure in a virtual machine or other computing platform. Data written to the blockchain can be public and/or can be encrypted and maintained as private. The temporary data that is used/generated by the smart contract is held in memory by the supplied execution environment, then deleted once the data needed for the blockchain is identified.

A chaincode may include the code interpretation of a smart contract, with additional features. As described herein, the chaincode may be program code deployed on a computing network, where it is executed and validated by chain validators together during a consensus process. The chaincode receives a hash and retrieves from the blockchain a hash associated with the data template created by use of a previously stored feature extractor. If the hashes of the hash identifier and the hash created from the stored identifier template data match, then the chaincode sends an authorization key to the requested service. The chaincode may write to the blockchain data associated with the cryptographic details (e.g., thus committing transactions 126, or a transaction of the transactions 126, etc.).

FIG. 1B illustrates an example of a blockchain transactional flow 150 between nodes of the blockchain in accordance with an example embodiment. Referring to FIG. 1B, the transaction flow may include a transaction proposal 191 sent by an application client node 160 to an endorsing peer node 181. The endorsing peer 181 may verify the client signature and execute a chaincode function to initiate the transaction. The output may include the chaincode results, a set of key/value versions that were read in the chaincode (read set), and the set of keys/values that were written in chaincode (write set). The proposal response 192 is sent back to the client 160 along with an endorsement signature, if approved. The client 160 assembles the endorsements into a transaction payload 193 and broadcasts it to an ordering service node 184. The ordering service node 184 then delivers ordered transactions as blocks to all peers 181-183 on a channel. Before committal to the blockchain, each peer 181-183 may validate the transaction. For example, the peers may check the endorsement policy to ensure that the correct allotment of the specified peers have signed the results and authenticated the signatures against the transaction payload 193.

Referring again to FIG. 1B, the client node 160 initiates the transaction 191 by constructing and sending a request to the peer node 181, which in this example is an endorser. The client 160 may include an application leveraging a supported software development kit (SDK), which utilizes an available API to generate a transaction proposal 191. The proposal is a request to invoke a chaincode function so that data can be read and/or written to the ledger. The SDK may reduce the package of the transaction proposal 191 into a properly architected format (e.g., protocol buffer over a remote procedure call (RPC)) and take the client's cryptographic credentials to produce a unique signature for the transaction proposal 191.

In response, the endorsing peer node 181 may verify (a) that the transaction proposal 191 is well formed, (b) the transaction has not been submitted already in the past (replay-attack protection), (c) the signature is valid, and (d) that the submitter (client 160, in the example) is properly authorized to perform the proposed operation on that channel. The endorsing peer node 181 may take the transaction proposal 191 inputs as arguments to the invoked chaincode function. The chaincode is then executed against a current state database to produce transaction results including a response value, read set, and write set. However, no updates are made to the ledger at this point. In some embodiments, the set of values, along with the endorsing peer node's 181 signature is passed back as a proposal response 192 to the SDK of the client 160 which parses the payload for the application to consume.

In response, the application of the client 160 inspects/verifies the endorsing peers signatures and compares the proposal responses to determine if the proposal response is the same. If the chaincode only queried the ledger, the application would inspect the query response and would typically not submit the transaction to the ordering node service 184. If the client application intends to submit the transaction to the ordering node service 184 to update the ledger, the application determines if the specified endorsement policy has been fulfilled before submitting. Here, the client may include only one of multiple parties to the transaction. In this case, each client may have their own endorsing node, and each endorsing node will need to endorse the transaction. The architecture is such that even if an application selects not to inspect responses or otherwise forwards an unendorsed transaction, the endorsement policy will still be enforced by peers and upheld at the commit validation phase.

After successful inspection, in the transaction payload step 193, the client 160 assembles endorsements into a transaction and broadcasts the transaction proposal 191 and response within a transaction message to the ordering node 184. The transaction may contain the read/write sets, the endorsing peers signatures and a channel ID (e.g., if a specific [off-chain] datastore is to be utilized, etc.). The ordering node 184 does not need to inspect the entire content of a transaction in order to perform its operation, instead the ordering node 184 may simply receive transactions from all channels in the network, order them chronologically by channel, and create blocks of transactions per channel.

The blocks of the transaction are delivered from the ordering node 184 to all peer nodes 181-183 on the channel. The transactions 194 within the block are validated to ensure any endorsement policy is fulfilled and to ensure that there have been no changes to ledger state for read set variables since the read set was generated by the transaction execution. Transactions in the block are tagged as being valid or invalid. Furthermore, in steps 195 each peer node 181-183 appends the block to the channel's chain, and for each valid transaction the write sets are committed to current state database. An event is emitted, to notify the client application that the transaction (invocation) has been immutably appended to the chain, as well as to notify whether the transaction was validated or invalidated.

Referring now to FIG. 2A, illustrated is an example of a decentralized fair marketplace 200, in accordance with embodiments of the present disclosure. As depicted, the decentralized fair marketplace 200 includes devices 202A-B, aggregators 204A-C, a decentralized platform 206, an users (e.g., buyers) 208A-C.

In some embodiments, the aggregators 204A-C register their respective pool of devices, e.g., devices 202A-B for aggregator 204A (it is noted that for ease of understanding that only aggregator 204A is depicted with devices, but aggregators 204B-C may also have their own pool of devices). In some embodiments, the users 208A-C publish their unique set of requirements (e.g., smart contract) on an energy ledger of the decentralized platform 206. In some embodiments, the smart contract matches any of the aggregators 204A-C to one or more bundles of resources (e.g., devices, energy, etc.) from any combination of the users 208A-C and auto-generates a new smart contract between an aggregator 204A-C and a user 208A-C.

In some embodiments, as depicted, the devices 202A-B (or a pool of devices) deliver the required power/energy to the users 208A-C and a hash of this delivery, along with a hash of an identity of the devices 202A-B, is shared on the energy ledger by a gateway, such as the gateway 254, which will be discussed more fully in regard to FIG. 2B.

In some embodiments, an aggregator 204A-C publishes the hash of delivered supplies to the users 208A-C who are part of the bundle on the energy ledger. In some embodiments, an aggregator 204A-C, who is a part of the bundle, generates a ZKP that proves the supplies are consistent with the data commitment done by the gateway for the individual devices that it has registered (as depicted, devices 202A-B for aggregator 204A). In some embodiments, an aggregator 204A-C generates one or more verifiable proofs for each user 208A-C that indicates that the terms and conditions of the smart contract are/have been met. The energy ledger verifies the proof and a final settlement is done.

Turning now to FIG. 2B, illustrated is an example of a ZKP based protocol 250 for proving correct execution of contracts, in accordance with embodiments of the present disclosure. As depicted, the ZKP based protocol 250 includes devices 252, a gateway 254, a ledger 256, and an aggregator 258. It is noted that like reference numerals are used to designate like parts in the accompanying drawings.

In some embodiments, the aggregator 258 has/owns the devices 252 and the aggregator 258 is matched with a bundle of users (e.g., user 1 and user 2). In this instance the bundle is joint bids from user 1 and user 2. In some embodiments, the devices 252 then deliver required resources (e.g., power) to users (e.g., buyers) and hash of this data, along with a hash of an identity of the devices 252 (e.g., H(DeviceId∥r1, data1)) is shared on the ledger 256 by the gateway 254.

In some embodiments, the aggregator 258 performs a commit 1 of the supply/delivery of resources to user 1 and a commit 2 of the supply/delivery of resources to user 2, which are recorded on the ledger 256. In some embodiments, the aggregator 258 then generates a ZKP that verifies that commit 1 and commit 2 are consistent; the ZKP is recorded/given to the ledger 256. In some embodiments, the aggregator 258 then generates a set of ZKPs for user 1 and user 2 that indicates that agreement specifications (e.g., a smart contract) are met; the set of ZKPS are then recorded/given to the ledger 256.

It is noted that the salient features of the solution provided by the ZKP based protocol 250 are that: a user/buyer doesn't know which devices 252 provided a supply to the user; the user doesn't know individual characteristics of any of the devices 252; the user is convinced that the agreement requirements are met (due to the ZKPs); and the aggregator 258 cannot fool the user if the requirements are not met.

Turning now to FIG. 2C, illustrated is an example of a Merkle tree commitment 270 of overall performance and individual user commitments, in accordance with embodiments of the present disclosure. As depicted, the Merkle tree commitment 270 includes devices (e.g., a pool of devices) performance hash 272, commits 274A-B, and hashes A-N. In some embodiments, the devices performance hash 272 is an overall performance hash captured on a blockchain, the commit 274A is a hash commitment made to a first user captured on the blockchain, the commit 274B is a hash commitment made to a second user captured on the blockchain, and the hashes 276A-N may be a <device id hash, performance data hash> tuple.

It is noted that in some embodiments, each <device id hash, performance data hash> tuple (e.g., hashes 276A-N) is submitted on/to the blockchain by a gateway entity. An aggregator then commits a Merkle tree root hash and commits 274A-B to the blockchain. The aggregator then generates a ZKP that in the overall Merkle tree commitment 270; it is noted that a value committed in leaf i and leaf (i+1) for i=1, 3, 5, . . . N is a valid tuple.

In regard to FIGS. 2A-C, and the disclosure as a whole, proposed is a non-interactive ZKP where any generic computation is represented as an arithmetic circuit (RICS). In some embodiments, standard libraries such as libiop or libsnark for generating the ZKP(s) are used. In some embodiments, commits/commitments may be public data hash commitments and hashes may be private data, e.g., individual performance data for the devices. In some embodiments, the generic computation on device data that is part of a commitment and must satisfy a specified requirement (e.g., based on a smart contract), for example, aggregate energy provided by all devices that are part of a commitment is more than a certain threshold, energy per minute is greater than specified threshold, etc.

In some embodiments, for each computation, an aggregator writes a program and generates the RICS using a known compiler such as Zokrates. The aggregator then uses a known ZKP library such as libsnark and libiop to generate the ZKPs. In some embodiments, a verifier can use the RICS, ZKPs and commitments to verify the computation.

In some embodiments, as proposed, the way data commitments are made allow for appropriate protocols to be designed that show there is no double tagging of devices to different users/buyers. Further, all the flow/solution is orchestrated on a blockchain.

The blockchain provides a way for all parties to make their hash commitments on a common channel (e.g., between a gateway, aggregator, and user). The ZKP for no double tagging is also submitted on this channel. Each user can use the hash commitment and the ZKP to check if operations are compliant. Otherwise, smart contract logic can verify the ZKPs and based on the smart contract logic take necessary actions (e.g., make a payment to an aggregator if everything is compliant).

In such a case, a ZKP uses the trusted data commitment made on the blockchain for both generating proof and verifying proof of a transaction (e.g., bundles to said user, energy to said devices, etc.). In some embodiments, data commitment is grounded on the blockchain where trusted parties can endorse their part of data.

Referring now to FIG. 3, illustrated is a flowchart of an example method 300 for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof, in accordance with embodiments of the present disclosure. In some embodiments, the method 300 may be performed by a processor, node, and/or peer node in a blockchain network/system (such as the decentralized fair marketplace 200 of FIG. 2A).

In some embodiments, the method 300 begins at operation 302, where the processor commits, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway. In some embodiments, the method 300 proceeds to operation 304, where the processor generates a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator.

In some embodiments, the method 300 proceeds to operation 306, where the processor executes individual commitments of a resource to a user. In some embodiments, the method 300 proceeds to operation 308, where the processor provides a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer, and the Merkle tree hash commitment match. In some embodiments, after operation 308, the method 300 may end.

In some embodiments, the method 300 may proceed to operation 310 where the processor (e.g., aggregator) may provide a second zero-knowledge-proof that proves that the commitments are mutually exclusive with no double utilization. In some embodiments, the method 300 proceeds to operations 312, where the processor may provide a third zero-knowledge-proof that proves agreement specifications from the user are met without revealing the identity or associated data of the resource producer. In some embodiments, after operation 312, the method 300 may end.

In some embodiments, discussed below, there are one or more operations of the method 300 not depicted for the sake of brevity. Accordingly, in some embodiments, the committing is a hash committing. In some embodiments, the Merkle tree hash commitment involves the identity of the resource producer and its associated data, and wherein a sub-tree in the Merkle tree hash commitment is associated with a commitment of individual resources. In some embodiments, the resource is two or more devices, the aggregator manages a pool of the two or more devices, and the user is a transmission system operator.

In some embodiments, the zero-knowledge-proof is a non-interactive zero-knowledge-proof, and the processor generates an arithmetic circuit from a ZoKrates compiler and generates the non-interactive zero-knowledge-proof.

In some embodiments, the processor identifies that a predetermined condition (e.g., smart contract) has been met and the processor automatically performs an action (e.g., where the action is an exchange of the resources).

It is to be understood that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present disclosure are capable of being implemented in conjunction with any other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.

Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of portion independence in that the consumer generally has no control or knowledge over the exact portion of the provided resources but may be able to specify portion at a higher level of abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.

Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).

Deployment Models are as Follows:

Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).

A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that includes a network of interconnected nodes.

FIG. 4A, illustrated is a cloud computing environment 410 is depicted. As shown, cloud computing environment 410 includes one or more cloud computing nodes 400 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 400A, desktop computer 400B, laptop computer 400C, and/or automobile computer system 400N may communicate. Nodes 400 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof.

This allows cloud computing environment 410 to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 400A-N shown in FIG. 4A are intended to be illustrative only and that computing nodes 400 and cloud computing environment 410 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

FIG. 4B, illustrated is a set of functional abstraction layers provided by cloud computing environment 410 (FIG. 4A) is shown. It should be understood in advance that the components, layers, and functions shown in FIG. 4B are intended to be illustrative only and embodiments of the disclosure are not limited thereto. As depicted below, the following layers and corresponding functions are provided.

Hardware and software layer 415 includes hardware and software components. Examples of hardware components include: mainframes 402; RISC (Reduced Instruction Set Computer) architecture based servers 404; servers 406; blade servers 408; storage devices 411; and networks and networking components 412. In some embodiments, software components include network application server software 414 and database software 416.

Virtualization layer 420 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers 422; virtual storage 424; virtual networks 426, including virtual private networks; virtual applications and operating systems 428; and virtual clients 430.

In one example, management layer 440 may provide the functions described below. Resource provisioning 442 provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing 444 provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal 446 provides access to the cloud computing environment for consumers and system administrators. Service level management 448 provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment 450 provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

Workloads layer 460 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation 462; software development and lifecycle management 464; virtual classroom education delivery 466; data analytics processing 468; transaction processing 470; and providing data privacy of contributors based on a zero-knowledge-proof 472.

FIG. 5, illustrated is a high-level block diagram of an example computer system 501 that may be used in implementing one or more of the methods, tools, and modules, and any related functions, described herein (e.g., using one or more processor circuits or computer processors of the computer), in accordance with embodiments of the present disclosure. In some embodiments, the major components of the computer system 501 may comprise one or more CPUs 502, a memory subsystem 504, a terminal interface 512, a storage interface 516, an I/O (Input/Output) device interface 514, and a network interface 518, all of which may be communicatively coupled, directly or indirectly, for inter-component communication via a memory bus 503, an I/O bus 508, and an I/O bus interface unit 510.

The computer system 501 may contain one or more general-purpose programmable central processing units (CPUs) 502A, 502B, 502C, and 502D, herein generically referred to as the CPU 502. In some embodiments, the computer system 501 may contain multiple processors typical of a relatively large system; however, in other embodiments the computer system 501 may alternatively be a single CPU system. Each CPU 502 may execute instructions stored in the memory subsystem 504 and may include one or more levels of on-board cache.

System memory 504 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 522 or cache memory 524. Computer system 501 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system 526 can be provided for reading from and writing to a non-removable, non-volatile magnetic media, such as a “hard drive.” Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), or an optical disk drive for reading from or writing to a removable, non-volatile optical disc such as a CD-ROM, DVD-ROM or other optical media can be provided. In addition, memory 504 can include flash memory, e.g., a flash memory stick drive or a flash drive. Memory devices can be connected to memory bus 503 by one or more data media interfaces. The memory 504 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of various embodiments.

One or more programs/utilities 528, each having at least one set of program modules 530 may be stored in memory 504. The programs/utilities 528 may include a hypervisor (also referred to as a virtual machine monitor), one or more operating systems, one or more application programs, other program modules, and program data. Each of the operating systems, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Programs 528 and/or program modules 530 generally perform the functions or methodologies of various embodiments.

Although the memory bus 503 is shown in FIG. 5 as a single bus structure providing a direct communication path among the CPUs 502, the memory subsystem 504, and the I/O bus interface 510, the memory bus 503 may, in some embodiments, include multiple different buses or communication paths, which may be arranged in any of various forms, such as point-to-point links in hierarchical, star or web configurations, multiple hierarchical buses, parallel and redundant paths, or any other appropriate type of configuration. Furthermore, while the I/O bus interface 510 and the I/O bus 508 are shown as single respective units, the computer system 501 may, in some embodiments, contain multiple I/O bus interface units 510, multiple I/O buses 508, or both. Further, while multiple I/O interface units are shown, which separate the I/O bus 508 from various communications paths running to the various I/O devices, in other embodiments some or all of the I/O devices may be connected directly to one or more system I/O buses.

In some embodiments, the computer system 501 may be a multi-user mainframe computer system, a single-user system, or a server computer or similar device that has little or no direct user interface, but receives requests from other computer systems (clients). Further, in some embodiments, the computer system 501 may be implemented as a desktop computer, portable computer, laptop or notebook computer, tablet computer, pocket computer, telephone, smartphone, network switches or routers, or any other appropriate type of electronic device.

It is noted that FIG. 5 is intended to depict the representative major components of an exemplary computer system 501. In some embodiments, however, individual components may have greater or lesser complexity than as represented in FIG. 5, components other than or in addition to those shown in FIG. 5 may be present, and the number, type, and configuration of such components may vary.

As discussed in more detail herein, it is contemplated that some or all of the operations of some of the embodiments of methods described herein may be performed in alternative orders or may not be performed at all; furthermore, multiple operations may occur at the same time or as an internal part of a larger process.

The present disclosure may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be accomplished as one step, executed concurrently, substantially concurrently, in a partially or wholly temporally overlapping manner, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Although the present disclosure has been described in terms of specific embodiments, it is anticipated that alterations and modification thereof will become apparent to the skilled in the art. Therefore, it is intended that the following claims be interpreted as covering all such alterations and modifications as fall within the true spirit and scope of the disclosure. 

What is claimed is:
 1. A system for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof, the system comprising: a memory; and a processor in communication with the memory, the processor being configured to perform operations comprising: committing, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway; generating a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator; executing individual commitments of a resource to a user; and providing a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer, and the Merkle tree hash commitment match.
 2. The system of claim 1, wherein the operations further comprise: providing a second zero-knowledge proof that proves that the commitments are mutually exclusive with no double utilization; and providing a third zero-knowledge-proof that proves agreement specifications from the user are met without revealing the identity or associated data of the resource producer.
 3. The system of claim 1, wherein the committing is a hash commitment.
 4. The system of claim 1, wherein the Merkle tree hash commitment involves the identity of the resource producer and its associated data, and wherein a sub-tree in the Merkle tree hash commitment is associated with a commitment of individual resources.
 5. The system of claim 1, wherein: the resource is two or more devices, the aggregator manages a pool of the two or more devices, and the user is a transmission system operator.
 6. The system of claim 1, wherein the zero-knowledge-proof is a non-interactive zero-knowledge-proof, and wherein the method further comprises: generating an arithmetic circuit from a ZoKrates compiler; and generating the non-interactive zero-knowledge-proof
 7. The system of claim 1, wherein the operations further comprise: identifying that a predetermined condition has been met; and performing, automatically, an action.
 8. A method for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof, the method comprising: committing, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway; generating a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator; executing individual commitments of a resource to a user; and providing a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer, and the Merkle tree hash commitment match.
 9. The method of claim 8, further comprising: providing a second zero-knowledge proof that proves that the commitments are mutually exclusive with no double utilization; and providing a third zero-knowledge-proof that proves agreement specifications from the user are met without revealing the identity or associated data of the resource producer.
 10. The method of claim 8, wherein the committing is a hash commitment.
 11. The method of claim 8, wherein the Merkle tree hash commitment involves the identity of the resource producer and its associated data, and wherein a sub-tree in the Merkle tree hash commitment is associated with a commitment of individual resources.
 12. The method of claim 8, wherein: the resource is two or more devices, the aggregator manages a pool of the two or more devices, and the user is a transmission system operator.
 13. The method of claim 8, wherein the zero-knowledge-proof is a non-interactive zero-knowledge-proof, and wherein the method further comprises: generating an arithmetic circuit from a ZoKrates compiler; and generating the non-interactive zero-knowledge-proof
 14. The method of claim 8, further comprising: identifying that a predetermined condition has been met; and performing, automatically, an action.
 15. A computer program product for trusted aggregation with data privacy of contributors based on a zero-knowledge-proof, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a function, the function comprising: committing, anonymously, an identity and associated data of a resource producer on a blockchain by an independent gateway; generating a Merkle tree hash commitment to the blockchain of all resources handled by an aggregator; executing individual commitments of a resource to a user; and providing a zero-knowledge-proof that proves that the commitment of the identity and associated data of the resource producer, and the Merkle tree hash commitment match.
 16. The computer program product of claim 15, wherein the function further comprises: providing a second zero-knowledge proof that proves that the commitments are mutually exclusive with no double utilization; and providing a third zero-knowledge-proof that proves agreement specifications from the user are met without revealing the identity or associated data of the resource producer.
 17. The computer program product of claim 15, wherein the committing is a hash commitment.
 18. The computer program product of claim 15, wherein the Merkle tree hash commitment involves the identity of the resource producer and its associated data, and wherein a sub-tree in the Merkle tree hash commitment is associated with a commitment of individual resources.
 19. The computer program product of claim 15, wherein: the resource is two or more devices, the aggregator manages a pool of the two or more devices, and the user is a transmission system operator.
 20. The computer program product of claim 15, wherein the zero-knowledge-proof is a non-interactive zero-knowledge-proof, and wherein the method further comprises: generating an arithmetic circuit from a ZoKrates compiler; and generating the non-interactive zero-knowledge-proof. 